Literature DB >> 23241526

Survival analysis of breast cancer patients using Cox and frailty models.

Javad Faradmal1, Atefeh Talebi, Abbas Rezaianzadeh, Hossein Mahjub.   

Abstract

BACKGROUND: Cox proportional hazard (CPH) model is the most widely used model for survival analysis. When there are unobserved/unmeasured individuals factor, then the results of the Cox proportional hazard model may not be reliable. The purpose of this study was to compare the results of CPH and frailty models in breast cancer (BC) patients.
METHODS: A historical cohort study was carried out using medical records gathered from the Fars Province Cancer Registry. The dataset consisted of 769 women having BC referred to Shiraz Namazi Hospital, south of Iran. These patients had been followed for 6 years. After selecting the most important prognostic risk factors on survival, CPH and gamma-frailty Cox models were used to estimate the effects of the risk factors.
RESULTS: The results of CPH model showed that, tumor characteristics and number of involved lymph nodes increase the mortality hazard of BC(P<0.05). In addition, the frailty model showed that there is at least a latent factor in the model (P=0.005).
CONCLUSION: Both of the frailty and CPH model emphasis that the early detection of BC improves survival in BC patients.

Entities:  

Mesh:

Year:  2012        PMID: 23241526

Source DB:  PubMed          Journal:  J Res Health Sci        ISSN: 2228-7795


  8 in total

1.  Survival Prediction and Feature Selection in Patients with Breast Cancer Using Support Vector Regression.

Authors:  Shahrbanoo Goli; Hossein Mahjub; Javad Faradmal; Hoda Mashayekhi; Ali-Reza Soltanian
Journal:  Comput Math Methods Med       Date:  2016-11-01       Impact factor: 2.238

2.  Model-based Recursive Partitioning for Survival of Iranian Female Breast Cancer Patients: Comparing with Parametric Survival Models.

Authors:  Mozhgan Safe; Javad Faradmal; Jalal Poorolajal; Hossein Mahjub
Journal:  Iran J Public Health       Date:  2017-01       Impact factor: 1.429

3.  Survival analysis in gastric cancer: a multi-center study among Iranian patients.

Authors:  Atefeh Talebi; Afsaneh Mohammadnejad; Abolfazl Akbari; Mohamad Amin Pourhoseingholi; Hassan Doosti; Bijan Moghimi-Dehkordi; Shahram Agah; Mansour Bahardoust
Journal:  BMC Surg       Date:  2020-07-13       Impact factor: 2.102

4.  Investigation of Prognostic Factors of Survival in Breast Cancer Using a Frailty Model: A Multicenter Study.

Authors:  Akram Yazdani; Mehdi Yaseri; Shahpar Haghighat; Ahmad Kaviani; Hojjat Zeraati
Journal:  Breast Cancer (Auckl)       Date:  2019-09-29

5.  Development of web-based dynamic nomogram to predict survival in patients with gastric cancer: a population-based study.

Authors:  Atefeh Talebi; Nasrin Borumandnia; Hassan Doosti; Somayeh Abbasi; Mohamad Amin Pourhoseingholi; Shahram Agah; Seidamir Pasha Tabaeian
Journal:  Sci Rep       Date:  2022-03-17       Impact factor: 4.379

6.  A Comparison between Cure Model and Recursive Partitioning: A Retrospective Cohort Study of Iranian Female with Breast Cancer.

Authors:  Mozhgan Safe; Javad Faradmal; Hossein Mahjub
Journal:  Comput Math Methods Med       Date:  2016-08-28       Impact factor: 2.238

7.  Application of Multi-State Model in Analyzing of Breast Cancer Data.

Authors:  Mahtab Vasheghani Farahani; Parisa Ataee Dizaji; Hamid Rashidi; Fariborz Mokarian; Akbar Biglarian
Journal:  J Res Health Sci       Date:  2020-01-05

8.  Social Determinants of Breast Cancer Screening among Married Women: A Cross-Sectional Study.

Authors:  Atefeh Ghanbari; Pardis Rahmatpour; Narges Hosseini; Malahat Khalili
Journal:  J Res Health Sci       Date:  2020-02-16
  8 in total

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